Scientist II, Modeling & Simulation

Entegris•Aurora, IL

6d•Onsite

About The Position

Entegris is seeking a Scientist II, Modeling & Simulation for its Aurora, Illinois facility. The Modeling & Simulation team applies computational methods to understand material properties, evaluate potential materials and formulations, and support semiconductor technology and product development. In this role, you will contribute to atomistic, molecular, and data modeling and simulation by applying established computational methods, models, and tools. You will work with experienced team members and cross-functional partners on projects involving a variety of materials and semiconductor applications. The position includes applying established approaches such as DFT, DFTB, Molecular Dynamics, and data modeling, as well as generating DFT training sets to support fine-tuning of Machine Learning Interatomic Potentials for Molecular Dynamics. You will also support the evaluation and use of AI-based tools for material development, analyze and communicate results, follow established procedures and documentation practices, and contribute to method improvements with guidance. The role requires an M.S. in a relevant technical field and working knowledge of computational modeling and simulation tools.

Requirements

M.S. in Chemistry, Materials Science, Chemical Engineering, Physics, or a related field, with a focus on computational chemistry, molecular dynamics, materials modeling, or a related discipline.
Working knowledge of atomistic, molecular, or data modeling and simulation using commercial or open-source software.
Familiarity with LINUX environments and one or more modeling and simulation tools such as LAMMPS, GROMACS, Quantum ESPRESSO, CP2K, VASP, xTB, or COSMO-RS/SAC.
Exposure to or familiarity with AI/ML tools and approaches used in material development, such as ChemProp, MLIP, FM4M, AiZynthFinder, Transformers, message-passing approaches, or self-attention architectures.
Working knowledge of Python or C/C++ for computational modeling, data analysis, or AI/ML applications; Python is preferred.
Strong communication and collaboration skills, including the ability to work effectively with different stakeholders and cross-functional teams.
Basic understanding of semiconductor processes and/or materials.
Ability to understand project requirements, apply established computational approaches to technical problems, and execute assigned work successfully.
Ability to analyze results, identify issues, and make appropriate adjustments with guidance from experienced team members.
Willingness to learn new modeling, simulation, and AI/ML tools and approaches, and apply techniques across different materials, products, and processes.
Commitment to continuous learning and development.

Nice To Haves

Experience with molecular design, retrosynthesis, data modeling, or material informatics.

Responsibilities

Execute established atomistic, molecular, and data modeling and simulation methods for material and technology development projects.
Work with experienced team members and project stakeholders to understand technical problems and translate defined requirements into modeling and simulation activities.
Apply established modeling approaches, including DFT, DFTB, Molecular Dynamics, and data modeling, to generate technical insights and support project objectives.
Generate DFT training sets to support fine-tuning of Machine Learning Interatomic Potentials (MLIP) for Molecular Dynamics modeling and simulation.
Support evaluation and application of AI-based tools for material development.
Analyze, document, and communicate modeling and simulation results to project team members and stakeholders.
Follow established models, parameters, codes, procedures, calculations, and documentation practices to support consistency and reuse.
Contribute to improvements in modeling and simulation methods based on project results, feedback, and technical guidance.
Collaborate with R&D staff, technologists, FAE, and other internal stakeholders on assigned projects.
Deliver accurate, high-quality modeling and simulation results within established project timelines and adjust work appropriately when issues are identified.